Performance based payment models (commonly referred to as performance-based financing (PBF) or results-based financing – (RBF)) are an important mechanism for helping to improve the quality of health services in low- and middle- income countries (LMICs) (Gergen, et al, 2017). PBF quality tools used in verification of facility performance are more focused on structural quality and availability of resources, with few processes of care. This has called for a need to improve the tools to focus more on the quality-of-care processes (Josephson, et al, 2017). Effect of performance-based payment interventions depend on its design, additional funding, supportive components such as technical support, and the context in which it is implemented (Diaconu et al, 2021). Based on lessons from implementation of PBF in several countries in LMICs, the need for ensuring that the quality components in PBF is adapted to a country context has been noted (Gergen, et al, 2018).
Analysis of data from Burundi, Lesotho, Senegal, Zambia and Zimbabwe have shown that PBF had no effect “on neonatal health outcomes, health care utilization or quality”, which indicates a need to relook at PBF if they are really effective (Gage and Bauhoff, 2021). However, a study by Brenner and colleagues on implementation of RBF in Malawi has shown that it has potential for improving “effective coverage” for obstetric services (Brenner, et al, 2021). In Zimbabwe, analysis of Demographic and Health Survey data between 2005 and 2015 was done to check for the effect of RBF implementation on health outcomes (neonatal, infant and under five mortality) and their analysis based on socio-economic groups. The findings have shown some positive effects on health outcomes but influenced by socio-economic status (Fichera, et al, 2021).
In Tanzania, PBF (in the name of pay for performance – P4P) intervention was introduced in Pwani Region in 2011 (Borghi, et al, 2013; Borghi, et al, 2021). Its implementation was shown to be influenced by the following “contextual factors”: salary and employment benefits; resource availability including staff, medicines and functioning equipment; supervision; facility access to utilities; and community preferences (Olafsdottir, et al, 2014). Other studies on its implementation found improvements in seven areas as follows. First, it improved accountability mechanisms in particular internal accountability mechanisms; external accountability mechanism improved in some aspects such as attitude to patients but did not influence functionality of Health Facility Governing Committees. (Mayumana, et al, 2017). Second, it reduced stock out of essential drugs in particular oxytocin; increased health care workers kindness at delivery; and also enabled supportive supervision visits to be implemented within planned timeframes (Anselmi, et al, 2017). Third, it improved availability of essential medicines and supplies, but had no effect on availability of functioning equipment. (Binyaruka and Borghi, 2017) Fourth, it was found to have potential for ensuring equity in accessing health services among the poor and in rural districts. (Binyaruka, et al, 2018) Fifth, it was found to have potential for influencing efficiency in particular in public facilities but it requires further improvement in its design for this to be realized. (Binyaruka, et al, 2020) Sixth, it produced some sustained improvements in user(patient) experience of care such as kindness. (Borghi, et al, 2021) Seventh, it showed potential for reducing women bypassing a nearby health facility. (Bezu, et al,2021). Given, its high costs in its implementation especially management costs and costs involved in performance data generation and verification, it was suggested to consider its integration in routine health systems so as to make it more cost-effective. (Borghi, et al, 2015)
Several studies looked at the way the P4P intervention in Tanzania was designed. A study by Songstad and colleagues (2012) on assessment of health care workers performance expectations with the P4P in comparison with the Open Performance Review and Appraisal System (OPRAS) found that the studied health care workers showed positive expectations towards P4P implementation, although the link between OPRAS and P4P was unclear. (Songstad, et al, 2012). However, the design was noted to be influenced by politics especially the influence of external actors in setting the agenda (Chimhutu, et al, 2015). Another study by Chimhutu, et al. (2016) found that the modality of distribution of bonuses in the P4P scheme was unfair and that it affected staff motivation, teamwork, as well as social relations at health facilities; which could ultimately affect the quality of health care services. Binyaruka and colleagues found that the design of how incentives are provided in P4P and some health facility characteristics influenced inequalities in health facilities performance (Binyaruka, et al, 2018). A study by Cassidy and colleagues observed that the roles of Health Facility Governing Committees were not included in the design of the P4P despite their key roles in enabling proper management of resources in health facilities and also linking with the community served. (Cassidy, et al, 2021). It was further found that apart from the potential for improving some aspects of experience of care, the way the P4P was designed with focus on certain services only, limited the generalizability of their gains in a whole health facility. (Chimhutu, et al, 2019)
Implementation of the P4P pilot in Pwani Region took place from 2011 to 2013 and thereafter, preparation for rolling on its improved version named RBF was started in which its pilot was done in two councils in Shinyanga Region in 2015 and rolled out to the whole region in 2016. The program was then rolled out to other regions as follows: Pwani, and Mwanza (2016); Geita, Kagera, and Kigoma (2017); Simiyu, and Tabora (2018). (Ministry of Health and Social Welfare, 2015[pp.51–52]) The RBF implementation in Tanzania gives payment to PHC facilities on quarterly basis based on their level of achievement that has been verified; in which 75% of the payments is allocated for facility improvement and 25% is for incentivizing the staff. (Ministry of Health, Community Development, Gender, Elderly and Children, 2019) By 2019, RBF was implemented in 8 regions of Tanzania: Pwani, Mwanza, Shinyanga, Tabora, Simiyu, Kagera, Kigoma, Geita. (Ministry of Health and Social Welfare, 2015; Ministry of Health, Community Development, Gender, Elderly and Children, 2019) The RBF implementation was envisaged as a strategy that can help to reform the health sector resulting in improvements in “service delivery, leadership and governance, human resources, health management information system, medical supplies, vaccines, equipment, and health care financing in order to improve accountability, efficiency, and equity”. (Ministry of Health and Social Welfare, 2015[pp.54])
This study aims to compare performance of health facilities in RBF regions and non-RBF regions in terms of quality of health services as measured by the Star Rating Assessment (SRA) approach. The SRA approach to quality was introduced in 2014 with the aim of assessing quality of health services in all Primary Health Care (PHC) Facilities in Tanzania. A baseline was conducted in the Fiscal Year 2015/2016 and reassessment was done in the Financial Year 2017/2018. (Yahya and Mohamed, 2018; Gage, et al, 2020) Specifically, the objectives of this study were to determine: (i) the difference in mean scores between the Star rating service areas in regions that implemented RBF versus those which did not implement in the health facilities in financial year 2017/18; (ii) whether there was an overall increment in 3 + star rating scores between baseline and follow up assessments; and whether there was difference in increment of 3 + star rating scores among regions that were exposed to RBF and those that were not between the two assessments.